Claude Opus 5.5 vs GPT-6.1 Sol: 2026 comparison

Claude Opus 5.5 and GPT-6.1 Sol in brief

Claude Opus 5.5 and GPT-6.1 Sol address similar needs: working with text, images and files, reasoning, and calling tools across long contexts. Their clearest differences in the supplied data concern pricing and evaluation results. GPT-6.1 Sol charges half as much for both input and output tokens and leads on several listed benchmarks. Claude Opus 5.5 has a slightly higher Epoch capability index. Choosing between them therefore requires weighing the measurements relevant to your work rather than treating either ranking as a universal verdict.

Claude Opus 5.5 : Claude Opus 5.5 (Anthropic): $4 / $20 per million tokens, 1M context, benchmarks, verdict and alternatives. Checked October 25, 2026.

GPT-6.1 Sol : GPT-6.1 Sol (OpenAI): $2 / $10 per million tokens, 1.1M context, benchmarks, verdict and alternatives. Checked October 25, 2026.

They are often weighed against each other by people who hesitate. This page lines up their features point by point (11 criteria), with no partnership with either publisher.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Capabilities (Epoch AI index)

Epoch AI's capabilities index rolls many benchmarks into one number: the higher, the better the model does on hard tasks. Claude Opus 5.5 : 168.8. GPT-6.1 Sol : 168.4. Edge: Claude Opus 5.5.

Shared benchmarks

On the benchmarks both models took, we count each one's wins. Claude Opus 5.5 : 0 of 6. GPT-6.1 Sol : 4 of 6. Edge: GPT-6.1 Sol.

Input price

The price of tokens sent to the model weighs heavily as soon as you send long documents or chat history. Claude Opus 5.5 : $4 / M tokens. GPT-6.1 Sol : $2 / M tokens. Edge: GPT-6.1 Sol.

Output price

Generated tokens usually cost several times more; they dominate the bill for writing and code. Claude Opus 5.5 : $20 / M tokens. GPT-6.1 Sol : $10 / M tokens. Edge: GPT-6.1 Sol.

Cost of a typical task

For a request of 2,000 input and 500 output tokens, repeated 30,000 times a month (1,000 a day). Claude Opus 5.5 : $540 per month. GPT-6.1 Sol : $270 per month. Edge: GPT-6.1 Sol.

Context window

The context window sets how much text the model reads at once: useful for long documents and agents. Claude Opus 5.5 : 1M tokens. GPT-6.1 Sol : 1.1M tokens. Edge: GPT-6.1 Sol.

Max output

The maximum answer length matters to generate long code files or reports. Claude Opus 5.5 : 128K tokens. GPT-6.1 Sol : 128K tokens. A tie on this point.

Accepted inputs

Text, images, files, audio: the more formats accepted, the more cases covered without extra tools. Claude Opus 5.5 : 3. GPT-6.1 Sol : 3. A tie on this point.

Tool calling

Essential for an agent: the model can call functions, APIs or MCP servers. Claude Opus 5.5 : yes. GPT-6.1 Sol : yes. A tie on this point.

Open weights

Downloadable weights let you run the model yourself, without sending data to a provider. Claude Opus 5.5 : no. GPT-6.1 Sol : no. A tie on this point.

Release date

A newer model often has fresher data and better training techniques. Claude Opus 5.5 : September 22, 2026. GPT-6.1 Sol : September 29, 2026. Edge: GPT-6.1 Sol.

In charts

Our analysis

The two models cover a similar set of declared functions. Anthropic released Claude Opus 5.5 on September 22, 2026, while OpenAI released GPT-6.1 Sol on September 29. Both accept text, images and files, and both support reasoning and tool calling. This makes either a candidate for applications that combine document analysis with model-directed actions. The profiles do not describe response style, sector-specific behavior or the reliability of particular tool workflows. Their shared feature list therefore establishes a comparable starting point, but does not demonstrate that they will handle your instructions or your documents with the same practical results.

GPT-6.1 Sol scores 95.4% on GPQA, 93.7% on FrontierMath, 73.9% on SimpleQA and 94.2% on ARC2. Claude records 90.6%, 91.2%, 72.2% and 93.3%, respectively. They tie at 100% on AIME and 98.5% on ARC1. The Epoch capability index gives Claude a narrow lead, at 168.83 against 168.37, showing that the aggregate and individual listed tests do not produce identical rankings. Claude costs $4 per million input tokens and $20 per million output tokens. GPT costs $2 and $10, respectively, making its listed token rates half as high for both categories at an equal volume.

Neither model has open weights, and the supplied information specifies no license for either one. These profiles therefore cannot establish detailed usage rights or deployment permissions. Both publishers are listed as US companies, but that does not identify where your content would be hosted or processed. Retention periods, deletion arrangements and any use of submitted material for training are also unspecified. If you plan to handle sensitive files, those conditions require a separate review. Nothing in the supplied data supports a privacy advantage for either model, and the shared input formats do not resolve those missing operational details.

Claude provides a context window of 1,000,000 tokens, while GPT provides 1,050,000. That difference may matter when your inputs approach the limit, although window size alone does not establish how well either model uses its contents. Both allow a maximum output of 128,000 tokens. For everyday integration, their declared inputs and functions are consequently close, while token pricing creates a clear cost difference at equal usage. Neither profile supplies latency, throughput or service availability figures. Evaluate representative documents and tool calls before deciding, particularly if the practical constraint that matters most to you is not covered by these benchmarks.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (Claude Opus 5.5 value / GPT-6.1 Sol value).

High request volume

Here, GPT-6.1 Sol has the edge: it wins 3 of the 3 criteria that matter in this situation, namely cost of a typical task ($540 per month / $270 per month), input price ($4 / M tokens / $2 / M tokens), and output price ($20 / M tokens / $10 / M tokens).

Hard tasks (reasoning, code)

Neither stands out on the criteria for this situation (capabilities (epoch ai index) (168.8 / 168.4), shared benchmarks (0 of 6 / 4 of 6), and max output (128K tokens / 128K tokens)): decide with a trial.

Agents and long documents

Here, GPT-6.1 Sol has the edge: it wins 1 of the 3 criteria that matter in this situation, namely tool calling (yes / yes), context window (1M tokens / 1.1M tokens), and accepted inputs (3 / 3).

Maximum privacy

Neither stands out on the criteria for this situation (open weights (no / no)): decide with a trial.

Which one to choose?

Choose Claude Opus 5.5 if…

• you value capabilities (epoch ai index) (168.8)

Claude Opus 5.5 is a reasonable candidate if the Epoch capability index carries weight in your selection and your inputs fit its one-million-token context. It supports the same listed input categories and core functions as GPT. Its higher token prices need justification through results on your own tasks, since the supplied profiles do not establish a corresponding practical advantage.

Choose GPT-6.1 Sol if…

• you value shared benchmarks (4 of 6)
• you value input price ($2 / M tokens)
• you value output price ($10 / M tokens)
• you value cost of a typical task ($270 per month)
• you value context window (1.1M tokens)

GPT-6.1 Sol makes sense if you want lower token costs while retaining text, image and file inputs, reasoning and tool calling. It also offers a slightly larger context window. Its stronger results on several supplied benchmarks, alongside ties on AIME and ARC1, provide concrete reasons to include it in an evaluation using your actual workload and operating constraints.

Strengths and limits of each

Claude Opus 5.5

• + Among the top 20% of models according to Epoch AI (ECI 168.8).
• + Very large context (1M tokens): long documents or a whole codebase fit in one request.
• + Agent-ready: tool calling and structured JSON output.
• − Expensive: costlier than 93 % of paid models.

GPT-6.1 Sol

• + Among the top 20% of models according to Epoch AI (ECI 168.4).
• + Very large context (1.1M tokens): long documents or a whole codebase fit in one request.
• + Agent-ready: tool calling and structured JSON output.
• − Expensive: costlier than 84 % of paid models.

The best test is still yours: take three real tasks from your day and give them to both for a week. The price calculator works out the gap on your own volume.

What about the others?

If neither suits you, look at GPT-6 Astra, Claude Fable 5.1, Gemini 4 Argon, Claude Sonnet 5.5, Claude Opus 5, and GPT-6 Sol.

Related comparisons:

• Gemini 4 Argon vs GPT-6.1 Sol
• Claude Opus 5.5 vs Gemini 4 Argon
• DeepSeek V4.1 Flash vs GPT-6.1 Sol
• Mistral Large 4 vs GPT-6.1 Sol
• Claude Opus 5.5 vs GPT-6 Astra
• Claude Opus 5.5 vs Muse Wonder

Conclusion

The available figures give GPT-6.1 Sol a clear pricing advantage and stronger results on several listed tests. Claude Opus 5.5 retains a small lead on the Epoch index, which alone cannot establish whether its higher rates are worthwhile for your needs. When both satisfy your functional requirements, compare representative outputs and tool workflows. Privacy conditions and operational performance remain unresolved because the profiles do not provide the necessary information.